Explored various resampling techniques to learn from an imbalanced dataset for detecting Credit card frauds.
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Updated
Jul 16, 2024 - Jupyter Notebook
Explored various resampling techniques to learn from an imbalanced dataset for detecting Credit card frauds.
Credit card fraud detection from european cardholders transactions
Parametric Contrastive Learning (ICCV2021) & GPaCo (TPAMI 2023)
Customer churn prediction is to measure why customers are leaving a business. In this tutorial we will be looking at customer churn in telecom business. We will build some models to predict the churn and use precision,recall, f1-score to measure performance of our model.
imFTP: Deep Imbalance Learning via Fuzzy Transition and Prototypical Learning (imFTP, Information Sciences 2024)
A (PyTorch) imbalanced dataset sampler for oversampling low frequent classes and undersampling high frequent ones.
A general interface for clustering based over-sampling algorithms.
Implementation of novel oversampling algorithms.
A general, feasible, and extensible framework for classification tasks.
Tugas praktikum Data Mining I
PySpark를 이용한 불균형 데이터 처리 알고리즘 구현
Fraud analytics for credit cards utilizes advanced algorithms and machine learning to monitor transaction patterns and detect suspicious activities. By analyzing real-time data, it identifies anomalies such as unusual spending behaviors, geographic inconsistencies, and high-risk transactions.
A multi-view panorama of Data-Centric AI: Techniques, Tools, and Applications (ECAI Tutorial 2024)
Implementation of a comparative analysis to find the best ML model for classifying dry eye disease from healthy controls using metabolomics datasets.
🛠️ Class-imbalanced Ensemble Learning Toolbox. | 类别不平衡/长尾机器学习库
[ICML'24] BAT: 🚀 Boost Class-imbalanced Node Classification with <10 lines of Code | 从拓扑视角出发10行代码改善类别不平衡节点分类
Synthetic data generation package to balance imblanaced datasets
Develop a model to predict which retail customers will respond to a marketing campaign. Logistic Regression shows the best performance.
Using Machine Learning in predicting customer churn from bank credit card services
Este repositório contém um código de Machine Learning que utiliza o algoritmo AllKNN do pacote imblearn para realizar o balanceamento de dados.
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